Multiscale convolutional neural networks for vision: based classification of cells

Authors:
Pierre Buyssens;Abderrahim Elmoataz;Olivier Lézoray
Affiliations:
GREYC UMR CNRS 6072 ENSICAEN --- Image Team, Université de Caen Basse---Normandie, Caen, France;GREYC UMR CNRS 6072 ENSICAEN --- Image Team, Université de Caen Basse---Normandie, Caen, France;GREYC UMR CNRS 6072 ENSICAEN --- Image Team, Université de Caen Basse---Normandie, Caen, France
Venue:
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Year:
2012

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Abstract

We present a Multiscale Convolutional Neural Network (MCNN) approach for vision---based classification of cells. Based on several deep Convolutional Neural Networks (CNN) acting at different resolutions, the proposed architecture avoid the classical handcrafted features extraction step, by processing features extraction and classification as a whole. The proposed approach gives better classification rates than classical state---of---the---art methods allowing a safer Computer---Aided Diagnosis of pleural cancer.